OpenHermes-2-Mistral-7B
| Property | Value |
|---|---|
| Base Model | Mistral-7B-v0.1 |
| License | Apache 2.0 |
| Training Data | 900,000 GPT-4 generated entries |
| Format | ChatML |
What is OpenHermes-2-Mistral-7B?
OpenHermes-2-Mistral-7B is a sophisticated fine-tuned language model built on the Mistral-7B architecture. Developed by Teknium, it represents a significant advancement in conversational AI, trained on an extensive dataset of 900,000 entries primarily generated by GPT-4. The model employs the ChatML format, enabling structured multi-turn dialogues with system-level instruction capabilities.
Implementation Details
The model utilizes extensive filtering of public datasets and converts all formats to ShareGPT, which is then transformed to use ChatML. This implementation allows for OpenAI endpoint compatibility and familiar interaction patterns for those experienced with ChatGPT API.
- Implements ChatML prompt format for structured dialogue
- Supports system-level instructions for consistent behavior
- Compatible with OpenAI endpoint specifications
- Available in multiple quantized versions (GPTQ, GGUF, AWQ)
Core Capabilities
- Outperforms previous Nous & Hermes models in benchmarks
- Achieves 72.68% on GPT4All benchmark
- Demonstrates strong performance in reasoning tasks
- Excels in multi-turn conversations with context retention
- Supports role-playing and creative writing scenarios
Frequently Asked Questions
Q: What makes this model unique?
OpenHermes-2 stands out due to its implementation of ChatML format, extensive training on GPT-4 generated data, and superior benchmark performance compared to other Mistral-7B variants. It shows particular strength in maintaining context and following system-level instructions.
Q: What are the recommended use cases?
The model excels in conversational AI applications, programming assistance, creative writing, role-playing scenarios, and complex reasoning tasks. It's particularly well-suited for applications requiring structured dialogue and consistent personality across interactions.
